Numerous clinical procedures involve needle insertion for diagnostic and therapeutic purposes. Such procedures include biopsies, regional anesthesia, drug delivery, blood sampling, prostate brachytherapy and ablation. These procedures require navigation and accurate placement of the needle tip at an organ, vessel or a lesion. The validity of a diagnosis or the success of a therapeutic treatment is highly dependent on the needle insertion accuracy. For example, in brachytherapy where radioactive seeds are deposited into the tumor by a needle, the effectiveness of the treatment is directly related to the accuracy of the needle placement. The same is obviously true in biopsy where needle misplacement may lead to misdiagnosis.
Physicians often perform the needle insertion procedure free-hand, advancing the needle according to the force feedback from the tool and their 3D perception of the anatomic structure. The performance of such procedures is limited, relying on the physician's training and skills Although imaging techniques can improve target visibility and needle placement, there still exist causes that contribute to needle misplacement, such as target movement and needle deflection due to tissue deformation. Furthermore, the trajectory may contain obstacles which need to be avoided, thus requiring reiteration of the insertion process. The variability of soft tissue properties may cause unpredictable discrepancy between the planned procedure phase and the treatment phase. It is estimated that of patients who underwent CT-guided needle biopsies, 14% of the tests were valueless due to needle misplacement. Therefore, biopsy procedures are sometimes repeated to ensure adequate sampling, exposing the patient to additional risks and potential complications.
Using a flexible rather than a rigid needle, the above limitations can be largely overcome since the flexible needle tip can be steered to the target, even along a curved trajectory, by maneuvering the needle base. PCT Patent Application No. PCT/IL2007/000682 for “Controlled Steering of a Flexible Needle” (published as WO2007/141784), and the article entitled “Image-guided Robot for Flexible Needle Steering”, by D. Glozman and M. Shoham published in IEEE Transactions on Robotics, Vol. 23, No. 3, June 2007, both herein incorporated by reference in their entirety, describe a robotic system for steering a flexible needle in soft tissue under real-time X-Ray fluoroscopic guidance.
This method, used for closed-loop needle insertion, utilizes an algorithm for robotic maneuvering of the needle base, based on a virtual spring model, path planning, needle tip and profile detection, and an iterative estimation of tissue stiffness by analyzing the displacement of the tissue along the length of the needle as a result of forces applied by the needle on the tissue.
A theoretical model for flexible needle steering in soft tissue, based on a virtual spring model, has been presented in the above referenced WO2007/141784. In this model, as illustrated in the schematic drawing of FIG. 1, the needle is held in the robotic base, which applies a lateral force Fb and a moment Mb to the needle. The needle itself is regarded as a linear beam divided into segments, labeled elements 1 . . . i . . . n, in FIG. 1, each of which is subject to lateral spring forces proportional to the virtual spring coefficient and the displacement. Assuming small lateral needle displacements, the tissue response is considered to be linear and the tissue forces are modeled by the lateral virtual springs distributed along the needle. Hence, each segment i, is subjected to point forces, Fi, which depend on the local displacement wi, from the initial position, woi, and the tissue stiffness, described by the virtual spring coefficient, ki.
From the boundary condition at the base, and the second order continuity conditions and spring forces applied between elements, 4×n equations can be derived, described by the following matrix expression:KN=Q  (1)where    n is the number of elements,    K is the matrix coefficients of Nij,    N is a vector of translation and slope at the edges of each element—Nij, where i is the element number and j is the degree of freedom at element i.    Q is a vector including a combination of stiffness coefficients and initial positions of the nodes at the times of their penetration with the needle.
Equation (1) can then be solved to calculate the required orientations and translations of the needle base so that the needle tip will follow the desired path. This is the inverse kinematics problem solution. Among all of the possible paths which avoid the obstacles and do reach the target, the optimal one to use is the path which applies minimal lateral pressure on the tissue, generally related to minimal needle curvature. This is achieved by selecting the tip inclination which minimizes the sum of squares of the virtual spring displacements and slopes.
However, the X-ray fluoroscope tracking described in the prior art involves X-radiation doses to the subject, and incidental scattered radiation exposure to the medical personnel performing the procedure. Additionally, availability of an X-ray system for performing the imaging may be limited, and such equipment is expensive, such that an alternative method of tracking the needle would be desirable.
The disclosures of each of the publications mentioned in this section and in other sections of the specification, are hereby incorporated by reference, each in its entirety.